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刘如明, 阚留杰, 崔国杰, 张国强, 涂春赵, 胡志爽. 渤海某油区井间地震作业环境噪声评级及应对措施[J]. 海洋石油, 2021, 41(2): 37-41, 47. DOI: 10.3969/j.issn.1008-2336.2021.02.037
引用本文: 刘如明, 阚留杰, 崔国杰, 张国强, 涂春赵, 胡志爽. 渤海某油区井间地震作业环境噪声评级及应对措施[J]. 海洋石油, 2021, 41(2): 37-41, 47. DOI: 10.3969/j.issn.1008-2336.2021.02.037
LIU Ruming, KAN Liujie, CUI Guojie, ZHANG Guoqiang, TU Chunzhao, HU Zhishuang. Classification of Ambient Noises and Operational Countermeasures for Offshore Cross-well Seismic Acquisition in an Oil Area of Bohai Sea[J]. Offshore oil, 2021, 41(2): 37-41, 47. DOI: 10.3969/j.issn.1008-2336.2021.02.037
Citation: LIU Ruming, KAN Liujie, CUI Guojie, ZHANG Guoqiang, TU Chunzhao, HU Zhishuang. Classification of Ambient Noises and Operational Countermeasures for Offshore Cross-well Seismic Acquisition in an Oil Area of Bohai Sea[J]. Offshore oil, 2021, 41(2): 37-41, 47. DOI: 10.3969/j.issn.1008-2336.2021.02.037

渤海某油区井间地震作业环境噪声评级及应对措施

Classification of Ambient Noises and Operational Countermeasures for Offshore Cross-well Seismic Acquisition in an Oil Area of Bohai Sea

  • 摘要: 海上钻完井作业及井场重型设备运行会产生各种类型的强噪声,常导致井间地震采集的数据由于信噪比过低而无法使用,需重新采集,从而影响了作业效率。渤海某油区利用井间地震前期采集的数据,同时结合钻完井作业及重型设备运行动态,分析出了不同噪声产生的方式和特征;然后根据噪声的强度、规律性、处理难度以及对数据质量的影响程度,将作业环境分为A、B、C、D四个评级,并针对不同级别环境噪声制定了应对措施,使后续数据采集作业有效规避了噪声,提高数据的信噪比,提升了作业效率。

     

    Abstract: Offshore drilling and completion operations and the operation of heavy equipment in the well site will produce various types of strong noise, which often leads to the failure of cross-well seismic data acquisition due to the low signal-to-noise ratio. As a result, the seismic data needs to be re-acquired, and that obviously affects the operation efficiency. Using the data collected in the early stage of cross-well seismic in an oil region of Bohai Sea, and combining with the drilling and completion operation and heavy equipment operation performance, the paper analyzes the ways and characteristics of different noise generation. According to the noise intensity, regularity, processing difficulty and the impact on data quality, the operation environment is divided into four grades: A, B, C and D, and corresponding countermeasures are formulated for different levels of environmental noise. Therefore, the subsequent data acquisition operations can effectively avoid the noise, increase the signal-to-noise ratio of data and improve the efficiency of the operation.

     

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